Characterizing Quantum Gates via Randomized Benchmarking

By Easwar Magesan, Jay M. Gambetta, Joseph Emerson. 2011

455 citations recorded by the source corpus.

We describe and expand upon the scalable randomized benchmarking protocol proposed in Phys. Rev. Lett. 106, 180504 (2011) which provides a method for benchmarking quantum gates and estimating the gate dependence of the noise. The protocol allows the noise to have weak time and gate dependence, and we provide a sufficient condition for the applicability of the protocol in terms of the average variation of the noise. We discuss how state-preparation and measurement errors are taken into account and provide a complete proof of the scalability of the protocol. We establish a connection in special cases between the error rate provided by this protocol and the error strength measured using the diamond norm distance.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/7003a5481db98d3b6e58c7b36ee289de3646dab7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Atomic and Molecular Physics, and Optics

Citations in the corpus

Leakage reduction in fast superconducting qubit gates via optimal control (2020, background): “[49] Magesan, E.”
The randomized measurement toolbox (2022, background): “Then it can be shown [92] that the slope of this decay curve estimates the average error rate between the noise E and the ideal gate U , defined as”
Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography (2016, background): “2a summarizes the gates’ steady improvement over this period by tracking their process infidelities [48], which corresponds to the RB error rate [49].”
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits (2021, background): “These systems need to be characterized [43] and calibrated [29] frequently to mitigate noise impacts.”
A universal qudit quantum processor with trapped ions (2021, methodology): “From the decay of the survival probability for increasingly long sequences of randomly chosen Clifford gate decompositions of identity, we estimate the average error per gate [26].”
Software Mitigation of Crosstalk on Noisy Intermediate-Scale Quantum Computers (2020, methodology): “rates, crosstalk exists between the two gates. Such measurements can be performed using Randomized Benchmarking (RB), a standard procedure for measuring gate error rates, which is used in IBM systems [29, 33, 34]. To measure the error rate, a single invocation of a gate is not enough. For CNOT error”
Noise tailoring for scalable quantum computation via randomized compiling (2015, result): “The lower bound is saturated by any stochastic Pauli noise, in which case the worst-case error rate is effectively equivalent to the experimental estimates obtained efficiently via randomized benchmarking [25].”